请问楼上各位大大，我的面板数据适合固定效应，不存在自相关，只有异方差，该怎么估计？如果异方差和自相关都存在又该怎估计？也请大家帮帮忙，我也正在做论文，急呀！在线等！多谢多谢啦！！！

是不是可以如arlionn那样:

先采用 xtdata 命令去除个体效果，再采用 xtgls 命令进行估计；

xtdata y x , fe

xtgls y x, p(c) 或xtgls y x, p(h) corr(ar1)

我在二楼的帖子已经更新，请查看

我也刚看到，谢谢arlionn的解答！

顶!

preserve

xtdata csr ac fsp ccp dp bs bm du mi pmc ls roe eps si grow , fe clear
（set mat 800,perm）
xtgls csr ac fsp ccp dp bs bm du mi pmc ls roe eps si grow, p(h) corr(ar1)

restore
我用的这个命令处理，固定效应的GLS怎么显示，variable year not found 呢？

[url][/url]留念一下

标记一下~~~~~~~~

挺有用的，但是如果要用工具变量，xtsacc还可行否

看到二楼的观点，想讨论一下。下面是从stata手册上摘的一段话：xtscc produces Driscoll and Kraay (1998) standard errors for coefficients
    estimated by pooled OLS/WLS or fixed-effects (within) regression. depvar
    is the dependent variable and varlist is an (optional) list of
    explanatory variables.

    The error structure is assumed to be heteroskedastic, autocorrelated up
    to some lag, and possibly correlated between the groups (panels). These
    standard errors are robust to very general forms of cross-sectional
    ("spatial") and temporal dependence when the time dimension becomes
    large. However, because this nonparametric technique of estimating
    standard errors does not place any restrictions on the limiting behavior
    of the number of panels, the size of the cross-sectional dimension in
    finite samples does not constitute a constraint on feasibility - even if
    the number of panels is much larger than T.  Nevertheless, because the
    estimator is based on an asymptotic theory one should be somewhat
    cautious with applying this estimator to panel datasets with a large
    number of groups that have only a short number of observations.
从这段解释应该说xtscc在N远大于T时应当慎用。

学习受教。

xtscc不能随便用吧

留念

搞不清，哎。

受教 mark一下~~

我也有同样的问题唉！怎么解决的呀？同学你解决了没？写论文，纠结。。。。

很好的解释，看来xtgls可以用来弥补xtreg, FE 上无法修正异方差和自相关的缺陷。

陈强老师的stata书里有些说明，《高级计量经济学及stata应用》P171

更符合法规和

mark

如果方程是非线性形式的是不是XTGLS就不能估计了？

mark